Although the obesity epidemic is ubiquitous in its reach, large disparities in obesity prevalence have nevertheless been observed among U.S. adolescents from different gender, racial/ethnic and socioeconomic groups. Several explanations for these disparities have been proposed, but research has yet to adequately explore the role of sleep duration in creating disparities in obesity prevalence. Because (1) sleep is a known risk factor for weight gain, and (2) sleep habits vary by gender, race/ethnicity, and socioeconomic status, research in this area promises to improve our understanding of obesity disparities. Disparities in obesity prevalence are a major public health concern, in part because obesity has been implicated as a risk factor for suboptimal physical and psychosocial well-being. Research has consistently shown that obese adolescents are substantially more likely than their healthy weight peers to report poor general health and physical functioning. Although studies have reported less consistent findings with regard to the psychosocial impact of obesity, some studies have also found impaired mental and social well-being among obese adolescents. Like obesity, sleep is also known to influence physical and psychological functioning. However, to date research has yet to explore how short sleep duration could amplify the adverse effects of obesity on adolescent well-being. Three major aims of our proposed analyses follow: Aim 1. Examine how sleep duration influences disparities in obesity that have been observed among groups of U.S. adolescents categorized by gender, race/ethnicity and socioeconomic status (SES). Aim 2. Develop and test a theoretical model of physical and psychosocial well-being among U.S. adolescents, where sleep moderates the direct impact of body mass. Aim 3. Examine whether the model developed in Aim 2 varies by gender, race/ethnicity and SES. To achieve these aims, we will utilize data from multiple waves of the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative study of U.S. adolescents in grades 7-12 in 1994-95. Add Health has followed this cohort of Americans into young adulthood, with the most recent wave of data collection occurring in 2008. With clinical measures of height and weight, repeated measures of sleep duration and quality, and a wide assortment of socioeconomic, demographic, psychological, and health indicators, Add Health is ideally suited for our research agenda. Our analyses will employ a number of advanced statistical techniques. For instance, to test a model of adolescent well-being (Aim 2), we will estimate a series of structural equation models that provide an empirical test of our theoretical expectations.